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Modeling Airborne Indoor and Outdoor Particulate Matter Using Genetic Programming Publisher



Karri RR1 ; Mohammadyan M3 ; Ghoochani M4 ; Mohammadpoure RA5 ; Yusup Y6 ; Rafatullah M6 ; Heibati B3 ; Sahu JN2
Authors
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Authors Affiliations
  1. 1. Petroleum & Chemical Engineering, Universiti Teknologi Brunei, Brunei Darussalam
  2. 2. University of Stuttgart, Institute of Chemical Technology, Faculty of Chemistry, Stuttgart, Germany
  3. 3. Health Science Research Center, Department of Occupational Health Engineering, Faculty of Health, Mazandaran University of Medical Sciences, Sari, Iran
  4. 4. Department of Environmental Health Engineering, Faculty of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  5. 5. Department of Biostatistics, Faculty of Health, Mazandaran University of Medical Sciences, Sari, Iran
  6. 6. Environmental Technology, School of Industrial Technology, Universiti Sains Malaysia, Pulau Pinang, 11800, Malaysia

Source: Sustainable Cities and Society Published:2018


Abstract

Airborne particulate matter (PM) is considered to be an essential indicator of outdoor and indoor air quality. In this study, indoor and outdoor PM1, PM2.5, PM10 concentrations were monitored at different locations within the Tehran University campus. It is found that 10% of PM1, PM2.5 and PM10 concentrations were higher than 36.11, 52.48 and 92.13 μg/m3 for indoors respectively. Genetic programming (GP) based methodology is implemented to identify the influence of outdoor PM on the indoor PM and established significant empirical models. The best GP model is identified based on fitness measure and root mean square error. It was observed that the GP based models are perfectly able to mimic the behavioural trends of outdoor particulate matter for PM1, PM2.5 and PM10 concentrations. The model predictions are very similar to the measured values and their variation was less than ± 8%. This analysis confirms the performance of GP based data driven modeling approach to predict the relationship between the outdoor particulate matter and its influence on the indoor particulate matter concentration. © 2018 Elsevier Ltd
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1. Assessment of Indoor and Outdoor Particulate Air Pollution at an Urban Background Site in Iran, Environmental Monitoring and Assessment (2017)